Inability to efficiently implement high-throughput field phenotyping is increasingly perceived as a key component that limits genetic gain in breeding programs. Field phenotyping must be integrated into a wider context than just choosing the correct selection traits, deployment tools, evaluation platforms, or basic data-management methods. Phenotyping means more than conducting such activities in a resource-efficient manner; it also requires appropriate trial management and spatial variability handling, definition of key constraining conditions prevalent in the target population of environments, and the development of more comprehensive data management, including crop modeling. This review will provide a wide perspective on how field phenotyping is best implemented. It will also outline how to bridge the gap between breeders and ‘phenotypers’ in an effective manner.

人们越来越多地认为，无法有效实施高通量田间表型分析是限制育种计划中遗传增益的关键因素。不仅要选择正确的选择特征，部署工具，评估平台或基本数据管理方法，还必须将现场表型整合到更广泛的环境中。表型化不仅仅意味着以资源有效的方式开展此类活动；它还需要适当的试验管理和空间变异性处理，定义在目标环境种群中普遍存在的关键约束条件，以及开发更全面的数据管理，包括作物建模。这篇综述将提供关于如何最好地实施表型的广泛观点。